The invention relates to personalizing and tailoring ETA information to a specific user based on driving data associated with the user, such as driving habits, driving tendencies, driving preferences, vehicle conditions, etc. For instance, a “personalized” ETA may be provided to the user by determining the personalized parameters of a mapping function.
Estimated Time of Arrival (“ETA”) is a measure of time when a vehicle, for example, is expected to arrive at a particular destination. ETA may be an important piece of information that a user, such as a driver or a passenger of the vehicle, may use to plan a trip. ETA information may also be updated at various points during the trip so as to allow the user to update travel plans accordingly along the way.
ETA related services may be provided by various map, location, or traffic applications. These applications may use different types of data and information to determine ETA. For example, ETA may be based on: (1) “static” data, or more generally, data associated with a map (e.g., route, distance, speed limit, traffic light positions and patterns, road geometry, turns, etc.), (2) “dynamic” data, or more generally, data associated with real-time traffic (e.g., incidents, accidents, weather, traffic, traffic flow rates, etc.), and/or (3) “crowd-sourcing” data, or more generally, data from numerous different users (e.g. taxis, private vehicles, drivers, passengers, etc.).
However, the above-noted applications may provide the same ETA information for many different users. In other words, the ETA information may be estimated regardless of user identity. In that regard, there is a need to determine ETA based on driving data associated with the user in order to provide more precise and more personalized ETA to the user while simultaneously preserving user privacy and sensitive user data.